FineReport

FEBRUARY 5, 2020

Users themselves drag and drop data from different sources to create analysis models, and then the system automatically processes the data through intelligent analysis and automatic correlation, including structured data and unstructured data. 2019’s Best Excel Reporting Tool that Reaches Far beyond Excel.

Metadata 98

Metadata Dashboards Informatics Visualization 98

Domino Data Lab

MARCH 3, 2019

Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019). AI Adoption in the Enterprise: How Companies Are Planning and Prioritizing AI Projects in Practice (Feb 2019). There are essentially four types encountered: image/video, audio, text, and structured data.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

erwin

OCTOBER 24, 2019

With an automated, real-time, high-quality data pipeline, enterprise stakeholders can base strategic decisions on a full inventory of reliable information. The post Very Meta … Unlocking Data’s Potential with Metadata Management Solutions appeared first on erwin, Inc.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Ontotext

SEPTEMBER 15, 2020

Data Fabric’ has reached where ‘Cloud Computing’ and ‘Grid Computing’ once trod. Data Fabric hit the Gartner top ten in 2019. Connecting the data in a graph allows concepts and entities to complement each other’s description. It is a buzzword.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Corinium

APRIL 25, 2019

It definitely depends on the type of data, no one method is always better than the other. For a large volume of structured data, for example, a customer master or data warehouse, where there are many stakeholders in your organization who need to see different subsets, tokenization is generally better.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

datapine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. quintillion bytes of data produced daily. followed by 18 zeros.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

IBM Big Data Hub

JULY 19, 2023

We started with prepping the proprietary structured data to clean and make it ready in a format to be able to pass within prompts for fine-tuning and inferencing. market were cleared between 2019 to 2022, with more than 300 apps in just four years. The high-level pipeline for this process is shown in Figure 1.

Consulting 61

Consulting Machine Learning Manufacturing Optimization 61

Ontotext

JULY 29, 2021

The two distinct threads interlacing in the current Semantic Web fabrics are the semantically annotated web pages with schema.org (structured data on top of the existing Web) and the Web of Data existing as Linked Open Data. Below, we outline the two directions in which we at Ontotext see and build the Semantic Web.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

AWS Big Data

JUNE 6, 2023

Technical challenges Data source specifics: The data in BigQuery is the export of GA 360 data and Firebase Analytics data. BigQuery uses a columnar storage format that can efficiently query semi-structured data, in the case of GA and Firebase data as arrays of structs.

Analytics 55

Analytics Data Lake Testing Optimization 55

CDW Research Hub

JULY 31, 2019

Natural Language Understanding (NLU) is a subset of NLP that turns natural language into structured data. inform{"startdate": "2019-10-03T00:00:00", "enddate": "2019-10-13T00:00:00"}. NLU is able to do two things?—?intent intent classification and entity extraction. utter_ask_who. inform{"people": "1"}. utter_ask_where.

Deep Learning 49

Deep Learning Machine Learning Testing Modeling 49

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44